Two-layer co-optimization method for a distributed energy system combining multiple energy storages

• Published in: Applied energy 2022-09, Vol.322, p.119486, Article 119486
• Main Authors: Guo, Jiacheng, Liu, Zhijian, Wu, Xuan, Wu, Di, Zhang, Shicong, Yang, Xinyan, Ge, Hua, Zhang, Peiwen
• Format: Article
• Language: English
• Subjects: Distributed energy system; Multiple energy storage systems; Nearly zero-energy community; Power-to-heat/cold; Two-layer co-optimization method
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2022.119486

[Display omitted] •A distributed energy system combining lithium battery and power-to-heat/cold was proposed.•The upper layer optimized the device configuration and underlayer storage operation parameter.•The objective value and decision variable volatility were under 5% and 30%, respectively.•Researched the comprehensive performance of the system in a nearly-zero energy community. With the rapid development of nearly zero-energy buildings, the establishment of a nearly zero-energy community composed of concentrated and contiguous nearly zero-energy buildings constitutes the future architectural trend. However, configuration and optimization research of distributed energy systems combining multiple energy storages (DES-MESs) for the nearly zero-energy community is not sufficiently mature. Therefore, this paper initially proposed a DES-MES combining power-to-heat, power-to-cold and lithium batteries. Subsequently, a two-layer co-optimization method was proposed considering the equipment configuration in the upper layer and energy storage operating parameters in the under-layer. Based on the nearly zero-energy community, the influence of the initial parameters on the DES-MES optimization results was studied. Then, comparative research of different co-optimization methods was conducted. Finally, analysed the interactive electricity quantity, annual cost, carbon dioxide emissions, etc., of the DES-MES under the nearly zero-energy community scenario. The results indicated that the stability of the performance indicators (volatility under 5.0%) and decision variables (volatility under 30.0%) of the system were much higher than those determined with multi-parameter or multi-stage co-optimization methods. Compared to the separated production system, the primary energy consumption and carbon dioxide emissions of the DES-MES were reduced by 4.7 × 106 kWh (72.3%) and 1.6 × 106 kg (79.0%), respectively. The two-layer co-optimization method could effectively solve the problem of balancing the accuracy of the optimization results and calculation time. This paper provides a solution for the study of the system structure, operation optimization, and performance indicators of the DES-MES under the nearly zero-energy community scenario.